Analysis of enterprise architecture evolution using markov decision processes

Abstract

Enterprise architecture (EA) offers steering instruments to aid architects in their decision-making process. However, the management of such a process is a challenging task for enterprise architects, due to the complex dependencies amongst EA models when evolving from an initial to a subsequent state. In this paper, we design, present and analyze an approach supporting EA model evolution. In doing so, we define EA artifacts dependencies and model their corresponding evolutions during change. Then, this model is processed using a feedback control schema to fully inform the EA design decisions. An access control model for an inventory case study is introduced to reason on issues connected to this evolution. The results obtained by a stochastic solution (Markov Decision Processes) are used to argue about the usefulness and applicability of our proposal.